Exploring wind data using the Meteostat
Group Members: Travis, Ira, Micah
Course: Data Science
Goal: Use ML models to predict wind trends in distinct U.S. regions
Source: Meteostat Python API
Dataset Type: Aggregated weather observations per station
Key Variableswspd: Average wind speed (mph)wdir: Mean wind direction (degrees)Time Period: 2024
Models: Wind Speed, Wind Direction, Locations
Frame: Hourly and Daily
Using Pittsburgh station
Missing Values
temp 0
dwpt 0
rhum 0
prcp 1091
snow 8761
wdir 0
wspd 0
wpgt 8761
pres 0
tsun 8761
coco 6
dtype: int64
Lagged 1, 3, and 6 hours before
TimeSeriesSplit with n_splits = 5
Linear Regression
MAE: 3.223
RMSE: 4.351
R²: 0.675
HistGradientBoostingRegressor
MAE: 2.649
RMSE: 3.906
R²: 0.743